France Travail Scraper — 700K+ FR Jobs API (Pôle Emploi)

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Scrape 700K+ job offers from France Travail (formerly Pôle Emploi) — the largest French public job board — via the official France Travail API. Get real competences, ROME code + label, lat/lon geo coords, structured salary, experience, education, sector in one call. Add optional AI fit-scoring, SIREN company intelligence, and incremental diff mode. No OAuth to configure, no API key for you, no monthly subscription.

✨ What makes this scraper different

Feature	This scraper	Other FT scrapers
Official France Travail API (structured, not HTML-guessed)	✅	❌ mostly HTML scraping
Real competences + ROME code + label per job	✅	❌
Structured salary (min, max, period, annualized_*)	✅	❌ raw string only
Geo coords (lat/lon) native, for each job	✅	❌
Experience years + education level detection	✅	❌
AI fit-scoring (candidate profile → 0-100 + apply/maybe/skip)	✅	❌
SIREN company intelligence (size, sector, status) per employer	✅	❌
Incremental diff mode (only new/changed, -70/95% cost)	✅	rare
Partner offers (Indeed, Apec) inclusion toggle	✅	partial
Success rate (live 30d)	100%	varies

What can this scraper do?

• 🇫🇷 700K+ live French job offers indexed by France Travail (CDI, CDD, alternance, intérim, stage)
• 🎯 11 search filters — keywords, location, contract, experience, qualification, salary, radius, posted since, full-time
• 🏷️ ROME code + label + real competences — straight from the official API taxonomy (not keyword guessing)
• 💰 Structured salary parsing — min, max, currency, period (year/month/hour), auto-annualized
• 📍 Native geo coordinates — lat/lon in every record, no extra geocoding step
• 🎓 Education level + experience years — from formations / experienceLibelle
• 🤖 AI fit-scoring (opt-in) — give a candidate profile, get a fit_score 0-100 + apply/maybe/skip per job
• 🏢 SIREN company intelligence (opt-in) — resolve each employer to size, sector (NAF), category, active/ceased status
• 🧭 ROME métier reference (opt-in, free) — canonical definition, alternative job titles, and France Travail's emerging skills per occupation (official ROME 4.0 API)
• 📊 Labour-market context (opt-in) — hires + jobseekers + recruitment-tension per ROME × department (official Marché du travail data): is this role in demand here?
• ♻️ Incremental diff mode (opt-in) — recurring runs emit only NEW/UPDATED offers, 70-95% cheaper monitoring
• 🚀 Zero setup for you — we carry the API credentials; you just click Start

What data can you extract per job?

Field	Description
id	France Travail offer ID
title	Job title
company	Employer name (or anonymized)
location / postal_code / department	City, postal code, département (75, 92, 13...)
geo	{ lat, lon, label } native from the API
contract_type / contract_type_label	CDI / CDD / MIS / SAI + human label
contract_nature / alternance	Contract nature + alternance flag
rome_code / rome_label / appellation	ROME job classification + label
salary	Raw salary text from France Travail
salary_parsed	{ min, max, currency, period, annualized_min, annualized_max, is_range }
competences	Structured skills from the API { code, libelle, exigence }
skills_detected	Flat skill list (competences + regex backfill, ≤25)
experience_years / experience_required	Min years + raw requirement label
education_level / formations	Detected level + structured formations
langues / permis	Required languages + driving licences
sector / naf_code	Sector label + NAF code
nombre_postes / accessible_th	Number of openings + disability-friendly flag
description	Full job description
apply_url	Direct application URL
posted_date / updated_date	YYYY-MM-DD
partner_source	Partner site (Indeed, Apec...) if applicable
rome	(opt-in) ROME 4.0 métier ref: { definition, appellations, skills_core, skills_emerging, work_contexts, riasec, isco_code, is_cadre, green_transition, digital_transition }
market	(opt-in) Labour-market context for the job's ROME × dept: { period, hires, hires_stable, jobseekers, tension_ratio, tension_label }
company_data	(opt-in) SIREN, size, sector, category, status — see AI/company sections
ai	(opt-in) { summary, seniority, remote, must_have, red_flags, fit_score, recommended_action }
change_type	(incremental mode) NEW / UPDATED / UNCHANGED / EXPIRED

How to scrape France Travail jobs in 5 steps

1. Create a free Apify account — no credit card required
2. Open France Travail Scraper on Apify Store
3. Set your filters — keyword (e.g. "développeur python"), location (75D for Paris dept), contract (CDI)
4. Pick maxResults (start with 20 to validate, scale to 5000 once happy)
5. Click Start — clean JSON in seconds, exportable to CSV / JSON / Excel from Apify dataset UI

How much does it cost to scrape France Travail jobs?

PAY_PER_EVENT — $0.0015 per job scraped ($1.50 per 1,000 results). Failed/empty runs not charged. Full structured detail (competences, ROME, geo, salary) is included in the base price — no enrichment upsell needed.

Run size	Jobs	Apify cost	Time
Quick test	20	$0.03	~3s
Standard	200	$0.30	~10s
Deep	1,000	$1.50	~40s
Massive	5,000	$7.50	~4min

Optional add-on events (charged only when you turn them on, on top of job-scraped):

Add-on	Event	Price	What you get
enrichCompany	company-enriched	+$0.002/job	Employer → SIREN, size, sector (NAF), category, active/ceased status
enrichMarket	market-enriched	+$0.002/job	Recruitment tension per ROME × dept (hires, jobseekers, tension ratio+label)
analyzeJobs	job-analyzed	+$0.01/job	AI summary, seniority, remote, red-flags + fit-score vs. candidate profile (paid Apify plan)

Incremental mode (incrementalMode=true) charges only NEW + UPDATED offers on recurring runs — typically 70-95% cheaper for daily monitoring.

Input parameters

Parameter	Type	Default	Description
keywords	string	—	Free-text search (title + description)
location	string	—	75D = Paris dept, 13D = Bouches-du-Rhône
contractType	string	—	CDI, CDD, MIS, SAI, multiple via comma
contractNature	string	—	E1 alternance, E2 apprentissage, FS formation
experience	enum	—	1 débutant, 2 exigé, 3 expérimenté
qualification	string	—	5 cadre, 3 technicien, etc.
fullTimeOnly	bool	false	Only full-time
minSalary	string	—	Annual minimum (30000)
radiusKm	string	—	Search radius from location
postedSince	enum	—	1, 3, 7, 14, 31 days
includePartners	bool	true	Include Indeed/Apec partner offers
enrichCompany	bool	false	Resolve each employer → SIREN + company data (company-enriched event)
enrichRome	bool	false	Attach ROME 4.0 métier reference (definition, appellations, emerging skills) — free
enrichMarket	bool	false	Attach labour-market tension per ROME × dept (market-enriched event)
analyzeJobs	bool	false	AI analysis + fit-scoring (job-analyzed event, paid plan)
candidateProfile	string	—	Candidate/role description for AI fit_score
incrementalMode	bool	false	Emit only NEW/UPDATED offers vs. last run
includeExpired	bool	false	Also emit EXPIRED markers (not charged)
stateKey	string	default	Baseline name for incremental mode
maxResults	integer	20	1–5000 (API caps a single query at ~1150)
enrichDetails	bool	false	HTML fallback only — API already returns full detail
proxyConfig	object	datacenter	HTML fallback only — France Travail rarely blocks

Output example

{
  "id": "ABCD123",
  "title": "Data Engineer Senior H/F",
  "company": "Acme Tech",
  "location": "Paris 9e (75009)",
  "geo": { "lat": 48.8775, "lon": 2.3380, "label": "Paris 9e Arrondissement" },
  "department": "75",
  "contract_type": "CDI",
  "salary": "De 55 000 € à 75 000 € sur 12 mois",
  "salary_parsed": {
    "raw": "De 55 000 € à 75 000 € sur 12 mois",
    "min": 55000, "max": 75000, "currency": "EUR",
    "period": "year", "is_range": true,
    "annualized_min": 55000, "annualized_max": 75000
  },
  "skills_detected": ["Python", "AWS", "Docker", "Kafka", "Snowflake", "SQL", "Airflow", "anglais"],
  "competences": [{ "code": "...", "libelle": "Python", "exigence": "E" }],
  "experience_years": 5,
  "education_level": "Bac+5 et plus ou équivalents",
  "rome_code": "M1805",
  "rome_label": "Études et développement informatique",
  "sector": "Programmation informatique",
  "apply_url": "https://acme.example/apply",
  "posted_date": "2026-06-19",
  "company_data": {
    "siren": "812345678", "legal_name": "ACME TECH SAS",
    "naf_code": "6201Z", "category": "PME", "employee_range": "100-199",
    "creation_date": "2015-03-01", "is_active": true, "risk_flag": null
  },
  "ai": {
    "summary": "Poste de data engineer senior pour bâtir la plateforme data.",
    "seniority": "senior", "remote": "hybrid",
    "must_have": ["Python", "AWS", "SQL"],
    "red_flags": [],
    "fit_score": 88, "fit_reason": "Stack Python/AWS alignée, séniorité correspondante.",
    "recommended_action": "apply"
  },
  "scraped_at": "2026-06-20T14:32:01Z"
}

company_data appears with enrichCompany=true, ai with analyzeJobs=true.

Use cases

• 🎯 ATS auto-feed — daily import of new CDI/alternance offers matching company hiring filters
• 💼 Recruitment intelligence — track who's hiring what in any ROME code / department
• 💰 Salary benchmarking — aggregate salary_parsed across thousands of jobs by role + region
• 🗺️ Geo job-map dashboards — leverage geo.lat/lon for interactive maps (Mapbox, Leaflet)
• 📊 Labor-market analytics — track open job count per ROME × department × month
• 🤖 Career bots — alert candidates daily when matching jobs are posted (combine with diff)
• 🎓 Career coaching SaaS — show students alternance/apprentissage matching their CAP/BTS

Use the actor via API

Python:

import requests

run = requests.post(
    "https://api.apify.com/v2/acts/dltik~francetravail-scraper/run-sync-get-dataset-items",
    headers={"Authorization": "Bearer YOUR_APIFY_TOKEN", "Content-Type": "application/json"},
    json={
        "keywords": "développeur python",
        "location": "75D",
        "contractType": "CDI",
        "experience": "2",
        "postedSince": "7",
        "enrichDetails": True,
        "maxResults": 50
    }
).json()
print(f"Scraped {len(run)} jobs")

curl:

curl -X POST "https://api.apify.com/v2/acts/dltik~francetravail-scraper/run-sync-get-dataset-items" \
  -H "Authorization: Bearer YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"keywords":"data engineer","location":"69D","contractType":"CDI","maxResults":100}'

FAQ

Does it use the official France Travail API? Yes. This scraper runs on the official France Travail API (api.francetravail.io Offres v2), so you get clean, fully-structured data — real competences, ROME code, native lat/lon, structured salary. We carry the API credentials, so there's nothing for you to register or rotate: you just click Start. If the API is ever unreachable, the actor automatically falls back to the public-HTML search so a run never fails.

Can I use my own France Travail API credentials? Yes — set FRANCETRAVAIL_CLIENT_ID and FRANCETRAVAIL_CLIENT_SECRET (from francetravail.io) as actor environment secrets and the actor will use them.

Does it cover alternance and stage? Yes, via contractNature (E1 alternance, E2 apprentissage, FS formation). All major contract types supported.

ROME code support? Every job comes back with its rome_code + rome_label from the official taxonomy, so you can group/aggregate by occupation. You can also search by ROME via the keywords filter.

Can I enrich the employer with company data? Yes — set enrichCompany=true and each employer is resolved to its SIREN with size, sector (NAF), category (PME/ETI/GE) and active/ceased status. Pair it with our Pappers Sirene Scraper or BODACC Scraper for full company financials and court-procedure history.

How fresh is the data? Pulled live at run time from the official France Travail API, so freshness matches France Travail itself. Use incrementalMode=true to poll daily and only pay for what changed.

Will France Travail block my runs? We've never been blocked at moderate volume (< 5000 jobs/run). Datacenter proxy is the default — toggle to residential only if you scrape at high frequency.

What's salary_parsed exactly? A structured breakdown of the raw salary string: detects ranges (30k-45k), single values (30000), periods (year/month/hour), and auto-annualizes to a comparable yearly figure. Unlike other scrapers, you can filter and sort numerically.

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License: MIT · Author: dltik